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Congregate living situations, such as homeless shelters, are high-risk settings for transmission of SARS-CoV-2 among residents and staff. This article describes findings from a study using active surveillance for SARS-CoV-2 that took place in 14 homeless shelters in King County, Washington, between 1 January and 24 April 2020.

Background: Partners In Health (PIH) committed to improving health care delivery in Maryland County, Liberia following the Ebola epidemic by employing 71 community health workers (CHWs) to provide treatment support to tuberculosis (TB), HIV and leprosy patients. PIH simultaneously deployed a socioeconomic assistance program with three core components: transportation reimbursement to clinics; food support; and additional social assistance in select cases.Objective: This study aimed to evaluate how a CHW program for community treatment support and addressing socioeconomic barriers to care can impact patient outcomes in a post-conflict and post-epidemic context. Methods: Retrospective observational study utilizing registry data from 513 TB, 447 HIV and 75 leprosy patients at three health facilities in Maryland County, Liberia. Treatment coverage and clinical outcomes for patient cohorts enrolled in the pre-intervention period (January 2015 to June 2015) and the post-intervention period (July 2015 to July 2017) are compared using logistic regression analyses. Results: TB treatment coverage increased from 7.7% pre-intervention to 43.2% (p < 0.001) post-intervention and lost to follow-up (LTFU) rates decreased from 9.5% to 2.1% (p = 0.003). ART treatment coverage increased 3.8 percentage points (p = 0.03), with patient retention improving 63.9% to 86.1% (p < 0.001); a 6.0 percentage point decrease in HIV LTFU was also observed (p = 0.21). Despite an 84.3% treatment success rate observed for leprosy patients, pre-intervention data was largely unavailable and statistical significance could not be reached for any treatment outcomes pre-post intervention. Conclusions: The PIH approach to CHW community treatment support in Liberia demonstrates how, with the right inputs, excellent clinical outcomes are possible even in postconflict and post-epidemic contexts. Care should be taken to position and support CHWs so that they have the opportunity to succeed, including full integration and recognition within the system, and the addition of clinical system improvements and social supports that are too often dismissed as unsustainable.

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This study failed to recruit enough cases and probably did not therefore have enough statistical power to detect an effect of the intervention. It was also based on a severely impaired sample with many comorbid problems. However, the results suggest that training community-based social workers in cognitive behaviour therapy is neither practical nor effective in improving the outcomes of their clients.

Background Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates. Methods We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel. Results 21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33.5%), Streptococcus pneumoniae (SPn, 29.0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9.6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load. Conclusions Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.

Background Rhinovirus (RV) is a common cause of respiratory illness in all people, including those experiencing homelessness. RV epidemiology in homeless shelters is unknown. Methods We analyzed data from a cross-sectional homeless shelter study in King County, Washington, October 2019-May 2021. Shelter residents or guardians aged ≥3 months reporting acute respiratory illness completed questionnaires and submitted nasal swabs. After April 1, 2020, enrollment expanded to residents and staff regardless of symptoms. Samples were tested by multiplex RT-PCR for respiratory viruses. A subset of RV-positive samples was sequenced. Results There were 1,066 RV-positive samples with RV present every month of the study period. RV was the most common virus before and during the COVID-19 pandemic (43% and 77% of virus-positive samples, respectively). Participants from family shelters had the highest prevalence of RV. Among 131 sequenced samples, 33 RV serotypes were identified with each serotype detected for ≤4 months. Conclusions RV infections persisted through community mitigation measures and was most prevalent in shelters housing families. Sequencing showed a diversity of circulating RV serotypes each detected over short periods of time. Community-based surveillance in congregate settings is important to characterize respiratory viral infections during and after the COVID-19 pandemic.

In challenging environments, LTFU can be reduced by CHW accompaniment and socio-economic assistance to patients with TB. Approaches are needed to improve cure verification in young patients and reduce mortality.